“Sneckdowns” and desire lines: A parable for the big data age

'Keep off the grass!', says the sign. But people, being people, don't always obey; and when...

‘Keep off the grass!’, says the sign. But people, being people, don’t always obey; and when they don’t, others follow. If the trespassers follow a regular route, most likely a shortcut, then the grass wears away – bare earth revealing the path of choice or what those who study such matters call a ‘desire line’.

The desire line is a natural form of crowd-sourced design and probably where the planners should have put the path in the first place.

Another example is something called a ‘Sneckdown’ – which is explained in a great post for the 99% Invisible site:

“Urban planners can learn a lot simply by observing where cars actually drive (or don’t) after a fresh snowfall. Author and activist Jon Geeting has been photographing ‘sneckdowns’ (a portmanteau of ‘snowy’ and ‘neckdowns’ or: curb extensions) in Philadelphia for years, highlighting areas that could be converted from vehicular to pedestrian use. Remarkably, his documentation has done far more than just create general interest — it has actually helped to reshape intersections.”

The sneckdown is the area of road which remains snowy because there are no cars driving over it. To put it another way, the area where traffic crushes the snow out of existence is the desire line – the portion of the road that drivers actually use.

In Philadelphia, campaigners were able to use the sneckdown photographs as evidence that pedestrian areas could be extended without impeding the flow of traffic – an act of urban reclamation with many benefits:

This is all rather wonderful, even ingenious, but does it have any wider relevance?

Yes, because it serves as a parable for the age of big data.

It won’t be long before we have a continuous stream of live information about our everyday interactions with the built environment and, indeed one another. Month by month, year by year, we’re adding to the automated array of cameras, microphones and other types of sensor that record what happens in the world about us – and our behaviour within it.

With these technologies in place it isn’t necessary to wait for a snowfall to work out the desire lines followed by pedestrians and drivers – it’ll all be there in a detailed log of our every movement.

However, as well as ensuring that this big data is anonymised, it needs to be made publicly available. While the paths we make in the snow are there for all to see and photograph, the electronic traces we leave behind could be hidden away for the exclusive use of state agencies or private corporations. If the big data that they collect is about us and the public spaces we share, then it is essential that we’re able to challenge and verify the conclusions that they draw from it.

In the not too distant future big data, plus the AI systems used to analyse it, will enable us to monitor and modify the public sphere in real time. To a growing extent it is already happening.